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navigating immersive 3D virtual environments (e.g., Roblox, Minecraft). Implement a parallelized agent-driven framework where multiple LLM-powered agents operate concurrently to explore user-generated worlds
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processes and understand their impact on survival, infection and resistance. We have developed approaches to study multiple bacterial pathogens in parallel, with a primary focus on Klebsiella pneumoniae and
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learning frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience inscalable data processing, including the use of parallel computing, cloud platforms,and distributed systems
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